Higher order reconstruction for MRI in the presence of spatiotemporal field perturbations

Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k‐space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, a...

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Published in:	Magnetic resonance in medicine Vol. 65; no. 6; pp. 1690 - 1701
Main Authors:	Wilm, Bertram J., Barmet, Christoph, Pavan, Matteo, Pruessmann, Klaas P.
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2011
Subjects:	algebraic image reconstruction Algorithms Brain Mapping - methods diffusion imaging DTI Echo-Planar Imaging Eddy current correction Feasibility Studies Humans Image Processing, Computer-Assisted - methods magnetic field monitoring Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Phantoms, Imaging
ISSN:	0740-3194, 1522-2594, 1522-2594
Online Access:	Get full text
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Abstract	Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k‐space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third‐order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate‐gradient algorithm that uses explicit matrix‐vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.
AbstractList	Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k-space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third-order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate-gradient algorithm that uses explicit matrix-vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k‐space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third‐order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate‐gradient algorithm that uses explicit matrix‐vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc. Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k-space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third-order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate-gradient algorithm that uses explicit matrix-vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration.Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k-space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third-order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate-gradient algorithm that uses explicit matrix-vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the traditional k ‐space picture of spatial encoding. Sources of higher order perturbations include eddy currents, concomitant fields, thermal drifts, and imperfections of higher order shim systems. In conventional MRI with Fourier reconstruction, they give rise to geometric distortions, blurring, artifacts, and error in quantitative data. This work describes an alternative approach in which the entire field evolution, including higher order effects, is accounted for by viewing image reconstruction as a generic inverse problem. The relevant field evolutions are measured with a third‐order NMR field camera. Algebraic reconstruction is then formulated such as to jointly minimize artifacts and noise in the resulting image. It is solved by an iterative conjugate‐gradient algorithm that uses explicit matrix‐vector multiplication to accommodate arbitrary net encoding. The feasibility and benefits of this approach are demonstrated by examples of diffusion imaging. In a phantom study, it is shown that higher order reconstruction largely overcomes variable image distortions that diffusion gradients induce in EPI data. In vivo experiments then demonstrate that the resulting geometric consistency permits straightforward tensor analysis without coregistration. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.
Author	Wilm, Bertram J. Pavan, Matteo Barmet, Christoph Pruessmann, Klaas P.
Author_xml	– sequence: 1 givenname: Bertram J. surname: Wilm fullname: Wilm, Bertram J. organization: Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland – sequence: 2 givenname: Christoph surname: Barmet fullname: Barmet, Christoph organization: Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland – sequence: 3 givenname: Matteo surname: Pavan fullname: Pavan, Matteo organization: Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland – sequence: 4 givenname: Klaas P. surname: Pruessmann fullname: Pruessmann, Klaas P. email: pruessmann@biomed.ee.ethz.ch organization: Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Snippet	Despite continuous hardware advances, MRI is frequently subject to field perturbations that are of higher than first order in space and thus violate the...
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SubjectTerms	algebraic image reconstruction Algorithms Brain Mapping - methods diffusion imaging DTI Echo-Planar Imaging Eddy current correction Feasibility Studies Humans Image Processing, Computer-Assisted - methods magnetic field monitoring Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Phantoms, Imaging
Title	Higher order reconstruction for MRI in the presence of spatiotemporal field perturbations
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